Quantitative Proteomics and Data Analysis

Laurent Gatto

Quantitative Proteomics and Data Analysis

Laurent Gatto – https://lgatto.github.io

Acknowledgements BBSRC for funding; Sebastian Gibb and Lisa Breckels for coding.

(Last update Mon Mar 28 21:59:44 2016)

These slides are available under a creative common CC-BY license. You are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) for any purpose, even commercially.

Content

  1. Introduction on data analysis
  2. Quantitative proteomics data analysis - overview
  3. Visualisation
  4. Quantitative proteomics data analysis - examples
  5. Data analysis
  6. References and resources

What is data analysis

The ability to prepare and explore data, identify patterns (good and pathological ones) and convince oneself that the pattern are genuine (rather than random).

To analyse data, you need

To analyse data, you need

To analyse data, you need

Quantitative proteomics data analysis

Quantitative proteomics data analysis

Visualisation

A picture is worth a thousand words.

Graphics reveal data.

Proteomics data analysis

Data analysis tools

should enables you to manipulate your data, give some guarantees about the integrity of the data, support effective extract/subset components of the data, visualise them, enable transformation of the data, give access to infrastucture for statistical analysis, and enable annotation of the data.

Data analysis basics

The MSnSet class for quantitative data

Can be subsetted, transformed, visualised, annotated, statistics, …

References

Resources